Almost 90 per cent of companies say they’re not getting anywhere with data analytics. What’s more, research by the Harvard Business Review found that the number of organizations that identify as “data-driven” has declined over the past three years.

“This is deeply disturbing,” said Chris St. Jeor, a data science consultant with Zencos, at a recent ITWC webinar. “We’ve got more data at our fingertips that ever before, yet it feels like we’re moving backwards.”

It’s also concerning because companies that rank higher on analytics maturity models tend to have better financial performance and are seen as top organizations among their peers.

Why aren’t organizations realizing the value from their data? There are common roadblocks, said St. Jeor. “But there are also success strategies that we have seen work over and over again to become more data driven.”

Three roadblocks and how to solve them

1. No leadership direction: To gain valuable insights from data analytics, there absolutely has to be a clear strategy in place, said St. Jeor. “We have met with so many companies that have gone out and purchased very fancy software, and they have no idea what to do with it,” he said. Successful strategies must be tied to business outcomes, incorporate modern tool sets and ensure staff readiness.

The best solution is to bring in an analytics coach, St. Jeor said. “They bring a wealth of experience, and they know the value that data provides to the business, and they’re able to bring that perspective to the team and create buy-in,” he said.

St. Jeor also advises organizations to start small with a short-term proof of concept that has an identifiable return on investment. The coach can help identify a high value project. “That’s what’s going to stoke the fires,” he said. “It’s going to create a thirst to receive that sort of output from your data.”

2.  Bad Data: A Gartner study found that the average company loses $15 million a year because of bad data. “The bottom line is that you need to get your data cleaned up, because bad data will simply lead to bad business decisions,” said St. Jeor. “You get out what you put in.”

There are three steps for organizations to get control of their data, St. Jeor said. First, create a team with members from all parts of the organization that fully owns the data quality process. Step two is to automate the process. Finally, he said that organizations must tear down data silos that prevent them from aggregating data. “It allows you to take a holistic view of your customers, your processes and your entire business structure,” he said. “This has been a tremendously successful approach.”

3.  Resistance to change and lack of skill sets: “The number one blocker that we often see is culture,” said St. Jeor. “It’s a stubbornness to adopt new ideas, or the kind of sentiment that whatever you’re trying to push is just the flavour of the month.” An analytics coach can help make sure the organization is set up for success by teaching employees how to search for opportunities to benefit from the data.

To address the skill set issue, St. Jeor recommends that organizations look within to create their own data science teams. “Look for the lifelong learners and turn them into your own unicorns,” he said. “Create a dynamic team and give your employees a stake in the game. This is what creates the culture of a powerful data driven organization.”